TUM Teaching
Our main aim in this section is to inform you about our practical courses at Technical University of Munich. For any course-related or technical-related questions, you can always reach out to us here.
The Practical Courses We Offer to Students at TU Munich
Advanced Practical Course - Enterprise Software Engineering at the example of SAP SS25
This course offers students a comprehensive insight into the development of business software using SAP as an example. During the course, students are introduced to the two SAP-specific programming models RESTful Application Programming Model (RAP) and Cloud Application Programming Model (CAP). RAP represents the modern way of developing SAP native applications on the S/4HANA system, while CAP focuses on the development of modern cloud applications. In the course of learning the programming models, students get to know the SAP-specific programming language ABAP and the front-end framework SAPUI5. ABAP (Advanced Business Application Programming) is the primary language used in SAP applications. Students learn the syntax, data structures and concepts of ABAP and develop basic skills for programming ABAP applications. SAPUI5 enables the development of modern, appealing and user-friendly web applications in the SAP environment. Students learn the basics of SAPUI5, including the development of user interfaces, data binding, navigation and the integration of SAP back-end services.
Advance Practical Course - Developing Innovative Services at the example of SAP Technologies SS25
Artificial intelligence and machine learning are the most growing topics of our time. The steadily increasing data growth combined with the ever shorter becoming time for software product releases in particular requires ever more effective and efficient data analyzes. Learning algorithms are already influencing our working world and our leisure time. In this practical course we want to deal with the basics of machine learning. In addition, we want to practice an entire machine learning pipeline and carry out our own short machine learning project based on practically relevant problems.